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Born & raised in Indianapolis,
IN
Graduate of IU – Kelley
School of Business with
Honor’s
MBA from University of
Indianapolis in Corporate
Finance
Manager, FP&A @ Weblink
International
8+ years experience in FP&A
and Accounting/Finance
Utilizing passions, skills, and
talents to help others realize
and achieve greatness!
About Me……….
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Presentation Agenda
1. What is Data Analytics & Business Intelligence
(BI)
2. Why is Data Analytics & Business Intelligence
(BI) Important?
• Business Intelligence Spectrum
3. What is the decision cycle?
4. Limitations of Data Analytics and BI
5. People Aspects of Data Analytics & BI
6. Process/Methods of Data Analytics & BI
7. Technology/Systems of Data Analytics & BI
8. Presentation Recap
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Data Analytics
• “There were 5 Exabyte of
information created
between the dawn of
civilization through 2003,
but that much information
is now created every 2
days.” – Eric Schmidt,
Google
Business Intelligence
• “BI is about providing the
right data at the right time
to the right people so they
can take the right
decisions.” - Nic Smith,
Microsoft
What is Data Analytics & Business Intelligence
(BI)?
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Why is Data Analytics Important?
Key Company Advantages for Data Analytics:
• Faster, smarter, and better decision making
• Foundation for scaled processes, insights, and analysis
• Establishing a “Learning” Company Culture
• Exploring new opportunities & mitigating threats/risks
Key techniques/methods for Data Analytics:
• Data Management
• Data Mining
• Predictive Analytics
• Data Cleaning & Storage
• Multiple data source aggregation & integration
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Why is Business Intelligence Important?
Key Company Advantages for Business Intelligence:
• Gain insights into customer behavior
• Improve visibility and transparency into KPI’s
• Turn data analytics into actionable information
• Improve operational execution and efficiency
Key techniques/methods for Business Intelligence:
• Business Planning & Direction
• Data Storage and Information Processing
• Technology focused
• Customer segmentation/Forecasting/Budgeting
• Accelerate the “Decision Cycle”
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Decision Cycle
The implementation of the decision cycle helps provide
financial and non-financial insights (i.e. customer
profitability, retention, addressable markets, etc.)
The decision cycle allows organizations to use data to
drive business decisions.
BI tools such as Microsoft Power BI, Tableau, Qlik, and
other tools help automate parts of the decision cycle.
Processes Data Information Knowledge Decision
Foundation ExecutionData Mining Data Analysis Learning
Data Analytics Business Intelligence
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Limitations of Data Analytics
Most companies source data requires manually extracting the data
then gathering that data into a spreadsheet.
Most excel spreadsheets are manual, meaning there is constant
extracting and updating for new data.
• Hourly, Daily, and Weekly data analysis and reporting requires a
lot of time to update
• During the updating process, spreadsheets are prone to human
error.
• Formula errors and troubleshooting is time consuming as you
have to identify the broken cell or formula to correct.
Employees have their own analysis and data sources so
consolidation is difficult. Ad hoc analysis tasks to see the entire
picture is difficult to perform.
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Lack to combine
multiple data sets
such as :
• Access Databases
• SQL Servers
• Excel Documents
• Teradata
• Oracle
• Salesforce
• And other sources
Limitation of Formal BI Systems
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People Aspects of Data Analytics & BI
“The evolution of finance is here to stay, and those
professionals/companies adapting to the new finance
frontier will be the ones who shape companies and
industries for years to come.” – Young Salsa
People Challenges
• Recruiting
• Retaining
• Developing
• Talent Deficit
• Change
• Business Partnership
• Finance Evolution
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Characteristics of Value
Integrators:
• Ability to adapt to
changing business
landscape and strategy
• Utilizes technology along
with high business
acumen to lead strategy
and operational execution
• Armed with Data Analysis
skills (Excel, SQL, Data
Mining, and Scaling
Analysis)
People Aspects of Data Analytics & BI contd.
Source: IBM CFO-CIO Leadership Exchange Survey, May 2013
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Processes are the
foundation for data
driven decision making.
Goal: to automate
process to information
to utilize high value
FP&A activities.
Process/Methods of Data Analytics & BI
Technology becomes
scalability avenue to
share knowledge and
learn.
Goal: to produce
framework for others to
leverage in data
decision making.
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2016 Business
Intelligence &
Analysis Magic
Quadrant
Detailed information
around BI & Data
Analytics solutions
evaluated on:
• Infrastructure
• Data Management
• Analysis & Content
Creation
Technology/Systems of Data Analytics & BI
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Trend of BI & Data Analysis Leaders
Highlights:
• Oracle has moved completely outside of the Leaders
quadrant.
• Microsoft continues to execute on completeness of vision
with other enhancements (Power Pivot, Power View).
• Qlik decreases ability to execute and implement over the
years.
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Presentation Recap
The high value activities in the decisions cycle are accelerating the
process to information phase, and spending more time and
resources in turning that information into knowledge. This
knowledge can then be used to make high value data drive
business decisions.
Leveraging technology in conjunction with sound processes and
data analytics allows companies to have access to data quickly and
accelerate the decision cycle.
Understanding the role people, process, and technology plays into
data analytics and business intelligence is important for all FP&A
professionals.
Lastly, accept and embrace that data analytics & business
intelligence is your friend and not your enemy.
Data Analytics: Science of examining raw data with the purpose of drawing conclusions about that information.
Business Intelligence: Technology driven process for analyzing data and presenting information to help business decision making.
Why it is important: Data analytics helps organizations harness their data and use it to identify new opportunities, evaluate threats, and data driven decision making.
Focusing on the right information by asking what’s important to your organization is a key point in obtaining better data decision making.
Many organization are flying blind when making decisions because they rely upon “gut” feelings and non-scalable solutions.
Data analysis and reporting provides a way to identify problems, assess the risk and share knowledge gained to assist your organization.
Accurate, actionable, and timely data drive businesses are vital to organization success.
Why it is important: Business Intelligence, BI is a concept that usually involves the delivery and integration of relevant and useful business information in an organization.
Companies use BI to detect significant events and identify/monitor business trends in order to adapt quickly to their changing environment and a scenario.
Limitations:
Lack of Scale
Data Integrity and Maintenance becomes full time job
Silo’s of data in different parts of the organization
Prone to human error or lack of knowledge sharing
Limitations:
Can’t look at the full picture of the company
Usually requires large capital investment in people, equipment, and maintenance.
IT people are usually the main people involved
Lack of adaptability in doing ad-hoc or customized analysis or insights.
Skilled needed for traditional finance and FP&A professionals is evolving into having strong understanding of data analytics techniques and methods and software solutions.
FP&A professionals that can leverage data analytics and work in their company of shaping business intelligence strategy will be the professionals that continue to drive the profession forward.
Gone are the days of finance professional being score keepers but value integrators.
Challenges:
Have identified process documented
Manual focused data analysis and lack of data source consolidated technology
No full version of the truth or full customer life cycle
Lack of consistent business practices or not high value from top-down
Techniques for DA:
Process Documentation
SQL access of information
Data Cleansing
Leaders:
Microsoft Power BI
Tableau
Qlik
I have worked with all the solutions in the leaders quadrant, and in my opinion Microsoft Power BI is the most complete solution to execute and implement.
Tell me we are not going to the presentation detailed where to download, assume this part is already done and when you get home it takes like 10 minutes get done.
